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01 / WE SERVE YOU AROUND THE WORLD
“The first rule of any technology used in a
business is that automation applied to an efficient
operation will magnify the efficiency.
The second is that automation applied to an
inefficient operation will magnify the inefficiency.”
– Bill Gates
https://www.youtube.com/watch?v=QPx4EcanXLg
Ch
ange
s in
Lat
itu
de
–C
han
ges
in A
ttit
ud
e
GLOBAL ANCILLARY REVENUES 2017
USD 82.2 BillionExpect $100+ BILLION in 2018
Source: The Amadeus Worldwide Estimate of Ancillary Revenue by Ideaworks
…People are willing to buy more!!
Ancillary Revenue – Here to Stay
Source: The Amadeus Worldwide Estimate of Ancillary Revenue by Ideaworks
Ancillary Revenue – Where Does It Come From?
Source: The Amadeus Worldwide Estimate of Ancillary Revenue by Ideaworks
Airlines Must Adapt their
Approach to Sales
Traditional Sales Model Innovative Sales Model
01 / WE SERVE YOU AROUND THE WORLD Step 1 KnowYour
Customers
Getting Data is Easy…Understanding Data is Hard• Airlines have a wealth of data available to them yet few know how to access it and
even fewer still how to understand it
• Data that is easily attainable:
• United Airlines uses a predictive analytics system that collects and detects up to 150 different variables to make up a customer persona profile
Search HistorySchedule
Preference
Bundled Packages
(Hotel/Car)
Airport Arrival Time
(Early/Late)
Purchase History O&D Trends
Frequent Flyer Points
(Earned/Used)
Solo Traveler or w/ Others
Checked Baggage
On Board Shopping
Travel Influencer
Social Media Connectivity
Give the Customer What THEY Want• Are you missing opportunities?
• Customer experience was identified by 61% of survey respondents as the top brand promise and the number 1 measure of customer loyalty*
• Personalization drives customer loyalty‒ Think back to our Amazon example‒ A fully engaged customer will more likely become a loyal customer
*Sabre/Forbes Insight Survey – Ascend Magazine, issue 2, 2017
Transit Companies (Taxi,
Uber, ETC.)
Airport Restaurant Discounts
Expedited Security/Immigra
tion for fee
Fare Rule Overrides
Airport Parking Lounge Access for
a day
“Flight of the day” Coupon Redemption
Baggage Courier Services
Step 2 - The –IZATION DilemmaCustomization versus Personalization
In 2015 a
major US
carrier
reported…
…yet generated HALF of
Carriers Total Revenue
111119 206
ATPCO WORKS AROUND THE WORLD
99% Over 99% of intermediated fares and over 87% of all
fares in the world are filed and distributed with ATPCO
170m The ATPCO-powered Fares & Rules system contains
over 170 million airline fares, composed of over 122
million public fares and almost 48 million private fares
THE GLOBAL MARKETPLACE IS EVOLVING
The airline of 2035 will look much different than those we know today
7.2 billion
passengers
2035
2016
3.8 billion
passengers
• The next generation of travel consumers will have grown up with technology much different than we did
• Advanced technologies and process driven changes are a must
Same Data
Different
Goals
Many airlines have valuable
data already in use within their
organization, but it is siloed.
Breaking down information
silos, sharing data, and setting
goals can be a place to start.
Identifying Existing Opportunities
Same Data, Different Goals
• Identify and understand what data is available across various entities
• Prioritize sharing this knowledge
• Select goals for each department and the data needed to achieve them• What information do I need to have a holistic view of my customers?
• Ownership under one entity • Master Data Management (MDM)
Same Data, Different Goals
Master Data Management (MDM)
Dat
a Q
ual
ity Ensuring Data is
accurate, up to date, and error free
Dat
a In
tegr
atio
n Marrying different pieces of structured and unstructured data together to create master view
Dat
a G
ove
rnan
ce Assigning ownership of data for maintenance, accessibility, improvement and enhancement of related processes
MDM
Data Quality
Data Integration
Data Governance
Customer Experience
Distribution and
EcommercePricing
Revenue Management
Sales and Marketing
How can shopping data be used by
each of the following entities?
Same Data, Different Goals
Same Data, Different Goals: Sales
• Online Sales/Offline Sales• Who could I be targeting that I am not?
• When is the best time for tactical sales promos?
• Alternatively, what is not working?
• Bundled packages • What is the data telling me about how passengers shop?
• Are there opportunities that I am missing to have initiatives that involve bundling? Is there a demand for it?
Same Data, Different Goals: Marketing
• Shopping data can be used within every day workflow
• Can be used to• Identify locations that are popular
• Marketing impacts after seeing where are they booking vs shopping
• How in advance are they booking
• Look to Book Ratio
Same Data, Different Goals: Revenue Management
• Shopping data can be incorporated into every day workflow• Dates that are in high demand
• What people shop for and what they actually book
• Last minute changes in demand
Same Data, Different Goals: Pricing
• Setting pricing strategy and using supporting data to leverage coding in ATPCO
• Understand what is coded in ATPCO vs what actually sells• Fares put into ATPCO do not always sell
• On average only about 5% of fares put into the marketplace actually sell
• IE using shopping data to adjust advance purchase dates
Same Data, Different Goals: Customer Experience
• What customers look at vs what they actually book
• Identifying customer purchasing behavior and finding patterns• INSERT Graphic from DJ email on African Passenger Behavior
• Look for opportunities for personalization for customers• IE Business passengers receiving discount for baggage inefficient
TYPES OF DATA
Schedules/Logistics ATPCO
Shopping Social Media
And MORE!
Types of Data
• What data is available within the organization?
• What data is not available? • Identify opportunities to acquire
data from outside sources when needed
• How do I aggregate social media data?
Search History/Purchase
HistoryO&D Trends
Schedule Performance
Baggage InfluencersBundled Packages
(Hotel/Car)
Frequent Flyer Program Stats
Social Media Customer
Behavior Trends (IE Arrival Time)
Types of Data
• Structured Vs Unstructured Data
Structured Data
Database Table
• Data that resides in fixed field within a record or file
• IE FF Program Data such as name, address, FF number
Unstructured Data
Social Media
• Blogs, tweets, comments, likes, followers, hashtags videos, images
Types of Data: Historical Data
• What are past trends and patterns in market behavior; commercial level• Routes
• Markets
• Cabin purchased
• Opportunities for “Bundling”
Types of Data: Ancillaries
• Baggage
• Food
• Seat Selection
• Legroom
• Branded Fares
Types of Data: Shopping Data
• What do customers shop for vs what do they actually book?
• When do they shop for it?
• What kind of passengers make the purchase? Business? Leisure?
• Look to book
• Web Analytics Systems and Applications capture this data
Types of Data: Sales Data
• What sells?
• What does not sell?
• What is changing in the marketplace?
• Are my competitors doing better or worse?
• Traditionally this data resides within Sales, Revenue Management, Revenue Accounting
Types of Data: Schedules/Routes
• What sells based on schedule?
• What does not?
• Does something need to change based on data received?
Types of Data: Social Media
• What are my customers saying about me?
• Are there videos, images that I can use?
• Where can I get this data?
• How do I analyze this data? Who can do this for me?
Types of Data: Customer Data
• What are past trends and patterns in customer behavior?
• Connecting customer total spending data with the customers profile for personalization to identify predictive analytics opportunities
• Segmenting by location demographics, past purchase behavior, and market behavior
• Identifying similar customer profiles and capturing trends
• Differences between personal travel or business for the same passenger
• Frequent Flyer program data• Option to gather customer data and create profile
Market Analysis
ENTEBBE -BUJUMBURA
Fares Filed Vs Sold
Filed FaresSold Fares
Workflow Optimization
How to optimize workflows to reduce time to market
03 / ATPCO
INNOVATION.
Change is an opportunity
as much as it is a challenge.
At ATPCO, we get excited about reimagining
the future of flight and the way people travel.
We innovate through a deep understanding of
the airline industry and the business needs of
the ecosystem.
NDC/NDC Exchange
Routehappy by ATPCODYNAMIC PRICING
A community platform where Airlines and Sellers exchange Offers/Orders
Real time Translations of differentmessage formats
Delivering reduced integration and maintenance costs
Enabling faster speed-to-market
NDC Exchange
NDC Use Cases
ROUTEHAPPY BY ATPCO Offers That People Want To Buy
RICHER SHOPPING EXPERIENCES FOR CONSUMERS
FARES AND
RULES
OPTIONAL
SERVICES
RICH CONTENT HAPPY FLYER
How they shop How they customize How they see it
What is Dynamic Pricing?
Offer Management – Ability to dynamically control offers to customers based on current real-time market variables
Five Defined Methods of Dynamic Pricing
1. More Frequent Fare Updates
2. Dynamic Availability
3. Dual RBD
4. Dynamic Pricing Engines
5. Dynamic Fare Generation
• Will require substantial process changes and development of new industry standards driving much higher costs and extended timelines
Dynamic Pricing
Example:
POINT 2 – Dynamic
Availability
Changes the RM
availability of fare products
based on characteristics of
booking requests
Dynamic Pricing
Frequent Flyer Programs are a Valuable Currency
Where to Find New Revenue?
EXPLORE THE
POSSIBILITIES
31.4% of passengers are enrolled in Voyageur FFP
accounting for 30% of total annual revenue
Reported approximately $50M USD from sales of
Extra Comfort and Preferred Seating
Sent FFP members over 250M emails in 2016.
An average of 9.3 emails per member.
Had 1M FFP members accrue points at BP petrol stations from APR 2015-
EOY 2016. Total members in program = 6.3M
Sold 10.5M chocolate bars (take rate of about 8%) and 8.9M cups of coffee (take rate of about 7%) in 2016
Source: Cartrawler/Ideaworks 2016 Yearbook of Ancillary Revenue
Innovation Effects Change
• Optimize both Product and Ticket level attributes
• Use available technologies‒ NDC, Dynamic Pricing and Rich Media Content (RouteHappy) are not just for others
• Break down silos between internal departments
‒ RM/Pricing/Sales/Marketing/eCommerce/Distribution must work together
• Look beyond traditional RM demand curves using predictive analytics
– Consider the entire customer experience – not just the flight
• Employ Data Scientists (or hire consultants) to assist
• Use Psychology to your advantageData
Achieving Your Ancillary Revenue Goals
• Understand the Opportunity‒ Ensure teams are aligned on the options available and that management embraces the change‒ Seek outside help to compile meaningful data that will produce tangible results
• Align the Brand to the Mission ‒ Change impacts everyone – customers, employees and investors‒ Any changes should be aligned to the core brand
• Find your Center‒ Executive direction is critical to build, manage and maximize ancillary revenue‒ Keep all teams aligned to the same goals
• Listen to Employees‒ They represent those closest to the customer, use that knowledge
• Learn from the Data‒ Offer products that the customer wants
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